The invention relates to a method for classifying a video sequence.
A video classification scheme for detecting commercials is described in U.S. Patent Application Publication US 2007/0261075A1.
Further video classification schemes are described in “New Real-Time Approaches for Video-Genre-Classification using High-Level Descriptors and a Set of Classifiers” (R. Glasberg, S. Schmiedeke, M. Mocigemba, T. Sikora: New Real-Time Approaches for Video-Genre-Classification Using High-Level Descriptors and a Set of Classifiers, IEEE International Conference on Semantic Computing, pages 120-127, 2008). In this paper different approaches for classifying videos are described in detail and compared to each other.
The great challenge in the field of multimedia content analysis is the transformation of human interpretations of audio-visual data to the respective machine processable representation. The difference between these two spheres is the so called “semantic gap”. Bridging this gap will open up a wide field of new applications. One possible application is the content selection in TV and World Wide Web according to user-specific profiles, e. g. genres like cartoon, commercial, music, news and sport. Humans perceive genres as patterns of audio-visual sequences describing dimensions like narration, aesthetics etc.